Signal filtering for a small-diameter, dual-axis FOG inclinometer

Chunhua Ren, Xiaoming Hu*, Poyun Qin, Leilei Li, Tong He

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

5 引用 (Scopus)

摘要

Purpose: Measurement-while-drilling (MWD) system has been used to provide trajectory and inclination parameters of the oil and gas well. Fluxgate magnetometer is a traditional choice for one MWD system; however, it cannot obtain effective trajectory parameters in nonmagnetic environments. Fiber-optic-gyroscope (FOG) inclinometer system is a favorable substitute of fluxgate magnetometer, which can avoid the flaws associated with magnetic monitoring devices. However, there are some limitations and increasing surveying errors in this system under high impact conditions. This paper aims to overcome these imperfections of the FOG inclinometer system. Design/methodology/approach: To overcome the imperfections, filtering algorithms are used to improve the precision of the equipment. The authors compare the low-pass filtering algorithm with the wavelet de-noising algorithm applied to real experimental data. Quantitative comparison of the error between the true and processed signal revealed that the wavelet de-noising method outperformed the low-pass filtering method. To achieve optimal positioning effects, the wavelet de-noising algorithm is finally used to inhibit the interference caused by the impact. Findings: The experimental results show that the method proposed can ensure the azimuth accuracy lower than ±2 degrees and the inclination accuracy lower than ± 0.15 degrees under the condition of interval impact. The method proposed can overcome the interference generated by the impact in the well, which makes the instrument suitable for the measurement of small-diameter casing well. Originality/value: After conducting the wavelet threshold filtering on the raw data of accelerometers, the noise generated by the impact is successfully suppressed, which is expected to meet the special requirement of the down-hole survey environment.

源语言英语
页(从-至)353-359
页数7
期刊Sensor Review
38
3
DOI
出版状态已出版 - 24 5月 2018
已对外发布

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